When does the influence of maturation on anthropometric and physical fitness characteristics increase and subside?

Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League

This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (n = 1052) from the 1034 matches played during the 2013–2017 seasons, along with data pertaining to the abovementioned player characteristics. Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1–20 and 21–40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41–60 and 61–80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development.

Biological maturation and match running performance: A national football (soccer) federation perspective

OBJECTIVES

To examine the influence of maturation and its interaction with playing position upon physical match performances in U15 footballers from a national federation.

DESIGN

Observational study.

METHODS

278 male outfield players competing in a national tournament were assessed for somatic maturity and match physical performances according to playing position. Stature, sitting height, and body mass were measured and entered into an algorithm to estimate the age at peak height velocity (APHV). Players match movements were recorded by Global Positioning System devices (10 Hz), to determine peak speed, and total- (TD), low-speed running (LSR; ≤13.0 km h^-1), high-speed running (HSR; 13.1-16.0 km h^-1), very high-speed running (VHSR; 16.1-20.0 km h^-1) and sprint distances (SPR; >20.0 km h^-1) expressed relative to match exposure (m min^-1).

RESULTS

Linear-mixed models using log transformed response variables revealed a significant contribution of estimated APHV upon TD (1.01; 95% CI: 0.99-1.02 m·min^-1; p < 0.001), HSR (1.05; 95% CI: 0.98-1.13 m min^-1; p < 0.001) and VHSR (1.07; 95% CI: 1.00-1.14 m min^-1; p = 0.047). An increase by one year in APHV was associated with an increase of 0.6, 5.4 and 6.9% in TD, HSR and VHSR respectively. No effects of APHV were observed for LSR, SPR, and peak speed. Further, no APHV effects were observed relative to players' field position.

CONCLUSIONS

Later maturing players covered substantially more higher-intensity (HSR and VHSR) running in matches, irrespective of playing position. The greater match intensity of later maturing players may inform talent identification and athletic development processes within a national federation.